如何根据 r 中不同行的条件删除 r 中组的最后一行

Question

我有一个这样的数据框（比如说，NT 和 MCS 是某个物种的文本占位符）

A <- c("NT", "MCS","MCS","NT", "MCS", "MCS", "NT", "MCS", "MCS", "MCS", 
       "NT", "MCS", "MCS","NT", "MCS","NT","NT","MCS", "MCS","NT")
B <- c("1", "3", "3","3","3", "3","3","4","4","4","4","3", 
       "3","3","2","2","1","3","3","3")
C <- c("G1", "G2", "G2", "G2", "G3", "G3", "G3", "G4", "G4", "G4", "G4", 
       "G5", "G5", "G5","G6", "G6", "G7","G8","G8","G8")

df <- data.frame(A,B,C)

A   B   C
NT  1   G1
MCS 3   G2
MCS 3   G2
NT  3   G2
MCS 3   G3
MCS 3   G3
NT  3   G3
MCS 4   G4
MCS 4   G4
MCS 4   G4
NT  4   G4
MCS 3   G5
MCS 3   G5
NT  3   G5
MCS 2   G6
NT  2   G6
NT  1   G7
MCS 3   G8
MCS 3   G8
NT  3   G8

A 列代表物种。 B 列表示一个整数值，等于每组中的行数。 C 列代表唯一组。标准如下：如果 B > 1，则删除每个组/物种的最后一行。如果 B = 1，则 NT（或该组中的唯一行）应保留。这是我需要的样子。

A   B   C
NT  1   G1
MCS 3   G2
MCS 3   G2
MCS 3   G3
MCS 3   G3
MCS 4   G4
MCS 4   G4
MCS 4   G4
MCS 3   G5
MCS 3   G5
MCS 2   G6
NT  1   G7
MCS 3   G8
MCS 3   G8

new<- df %>% group_by(A, B) %>% slice(if(any(numb > 1)) 1:n())

上面是我运行过的最接近的代码，但它不会计算为整数或数字向量（这是我需要它做的）。我是这样做的：

new <- df %>% group_by(A, B) %>% 
              slice(if(any(B > 1)) 1 else 1:n())

但它摆脱了重复的值（所以我不想删除 A 列中的所有值 - 无论是否重复，都不是最后一行）。我运行的代码中是否缺少某些东西或可以实现此目的的另一种方法（理想情况下在 dplyr 中，但我会对所有方法感到好奇）？

Answer 1

df %>% group_by(C) %>% slice(if(n() > 1) 1:(n()-1) else 1)

或

library(data.table)
setDT(df)

df[, if (.N > 1) head(.SD, -1) else .SD, by = C]

或用于max speed（还顺便保持列顺序）

df[df[, if (.N > 1) head(.I, -1) else .I, by = C]$V1]

Answer 2

有了dplyr，我们也可以这样做

library(dplyr)
df %>%
     group_by(C) %>%
     slice(union(1, head(seq_len(n()), -1)))

---

或filter

df %>%
   group_by(C) %>%
   filter(row_number() != n() | n()==1)